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  <div class="section" id="cortex-built-ins-networks-package">
<h1>cortex.built_ins.networks package<a class="headerlink" href="#cortex-built-ins-networks-package" title="Permalink to this headline">¶</a></h1>
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
</div>
<div class="section" id="module-cortex.built_ins.networks.SpectralNormLayer">
<span id="cortex-built-ins-networks-spectralnormlayer-module"></span><h2>cortex.built_ins.networks.SpectralNormLayer module<a class="headerlink" href="#module-cortex.built_ins.networks.SpectralNormLayer" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="cortex.built_ins.networks.SpectralNormLayer.SNConv2d">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.SpectralNormLayer.</code><code class="descname">SNConv2d</code><span class="sig-paren">(</span><em>*args</em>, <em>n_power_iterations=1</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/SpectralNormLayer.html#SNConv2d"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.SpectralNormLayer.SNConv2d" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.conv.Conv2d</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.SpectralNormLayer.SNConv2d.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/SpectralNormLayer.html#SNConv2d.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.SpectralNormLayer.SNConv2d.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.SpectralNormLayer.SNLinear">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.SpectralNormLayer.</code><code class="descname">SNLinear</code><span class="sig-paren">(</span><em>*args</em>, <em>n_power_iterations=1</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/SpectralNormLayer.html#SNLinear"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.SpectralNormLayer.SNLinear" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.linear.Linear</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.SpectralNormLayer.SNLinear.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/SpectralNormLayer.html#SNLinear.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.SpectralNormLayer.SNLinear.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.SpectralNormLayer.l2normalize">
<code class="descclassname">cortex.built_ins.networks.SpectralNormLayer.</code><code class="descname">l2normalize</code><span class="sig-paren">(</span><em>v</em>, <em>esp=1e-08</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/SpectralNormLayer.html#l2normalize"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.SpectralNormLayer.l2normalize" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.SpectralNormLayer.sn_weight">
<code class="descclassname">cortex.built_ins.networks.SpectralNormLayer.</code><code class="descname">sn_weight</code><span class="sig-paren">(</span><em>weight</em>, <em>u</em>, <em>height</em>, <em>n_power_iterations</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/SpectralNormLayer.html#sn_weight"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.SpectralNormLayer.sn_weight" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.ae_network">
<span id="cortex-built-ins-networks-ae-network-module"></span><h2>cortex.built_ins.networks.ae_network module<a class="headerlink" href="#module-cortex.built_ins.networks.ae_network" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="cortex.built_ins.networks.ae_network.AENetwork">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.ae_network.</code><code class="descname">AENetwork</code><span class="sig-paren">(</span><em>encoder</em>, <em>decoder</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/ae_network.html#AENetwork"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.ae_network.AENetwork" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.ae_network.AENetwork.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em>, <em>nonlinearity=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/ae_network.html#AENetwork.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.ae_network.AENetwork.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.base_network">
<span id="cortex-built-ins-networks-base-network-module"></span><h2>cortex.built_ins.networks.base_network module<a class="headerlink" href="#module-cortex.built_ins.networks.base_network" title="Permalink to this headline">¶</a></h2>
<p>A base network for handling common arguments in cortex models.</p>
<p>This is not necessary to use cortex: these are just convenience networks.</p>
<dl class="class">
<dt id="cortex.built_ins.networks.base_network.BaseNet">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.base_network.</code><code class="descname">BaseNet</code><span class="sig-paren">(</span><em>nonlinearity='ReLU'</em>, <em>output_nonlinearity=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/base_network.html#BaseNet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.base_network.BaseNet" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>Basic convenience network for cortex.</p>
<dl class="attribute">
<dt id="cortex.built_ins.networks.base_network.BaseNet.models">
<code class="descname">models</code><a class="headerlink" href="#cortex.built_ins.networks.base_network.BaseNet.models" title="Permalink to this definition">¶</a></dt>
<dd><p>A sequence of</p>
</dd></dl>

<dl class="method">
<dt id="cortex.built_ins.networks.base_network.BaseNet.add_linear_layers">
<code class="descname">add_linear_layers</code><span class="sig-paren">(</span><em>dim_in</em>, <em>dim_h</em>, <em>dim_ex=None</em>, <em>Linear=None</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/base_network.html#BaseNet.add_linear_layers"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.base_network.BaseNet.add_linear_layers" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

<dl class="method">
<dt id="cortex.built_ins.networks.base_network.BaseNet.add_output_layer">
<code class="descname">add_output_layer</code><span class="sig-paren">(</span><em>dim_in</em>, <em>dim_out</em>, <em>Linear=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/base_network.html#BaseNet.add_output_layer"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.base_network.BaseNet.add_output_layer" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

<dl class="method">
<dt id="cortex.built_ins.networks.base_network.BaseNet.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x: torch.Tensor</em>, <em>nonlinearity: str = None</em>, <em>**nonlinearity_args</em><span class="sig-paren">)</span> &#x2192; torch.Tensor<a class="reference internal" href="_modules/cortex/built_ins/networks/base_network.html#BaseNet.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.base_network.BaseNet.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

<dl class="method">
<dt id="cortex.built_ins.networks.base_network.BaseNet.get_h">
<code class="descname">get_h</code><span class="sig-paren">(</span><em>dim_h</em>, <em>n_levels=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/base_network.html#BaseNet.get_h"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.base_network.BaseNet.get_h" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

</dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.base_network.make_subnet">
<code class="descclassname">cortex.built_ins.networks.base_network.</code><code class="descname">make_subnet</code><span class="sig-paren">(</span><em>from_network</em>, <em>n_layers</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/base_network.html#make_subnet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.base_network.make_subnet" title="Permalink to this definition">¶</a></dt>
<dd><p>Makes a subnet out of another net.</p>
<p>Shares parameters with original network.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>from_network</strong> – Network to derive subnet from.</li>
<li><strong>n_layers</strong> – Number of layers from network to use.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">A Subnet for the original network.</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.conv_decoders">
<span id="cortex-built-ins-networks-conv-decoders-module"></span><h2>cortex.built_ins.networks.conv_decoders module<a class="headerlink" href="#module-cortex.built_ins.networks.conv_decoders" title="Permalink to this headline">¶</a></h2>
<p>Convolutional decoders</p>
<dl class="class">
<dt id="cortex.built_ins.networks.conv_decoders.SimpleConvDecoder">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.conv_decoders.</code><code class="descname">SimpleConvDecoder</code><span class="sig-paren">(</span><em>shape</em>, <em>dim_in=None</em>, <em>initial_layer=None</em>, <em>dim_h=64</em>, <em>nonlinearity='ReLU'</em>, <em>output_nonlinearity=None</em>, <em>f_size=4</em>, <em>stride=2</em>, <em>pad=1</em>, <em>n_steps=3</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/conv_decoders.html#SimpleConvDecoder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.conv_decoders.SimpleConvDecoder" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#cortex.built_ins.networks.base_network.BaseNet" title="cortex.built_ins.networks.base_network.BaseNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">cortex.built_ins.networks.base_network.BaseNet</span></code></a></p>
<dl class="method">
<dt id="cortex.built_ins.networks.conv_decoders.SimpleConvDecoder.next_size">
<code class="descname">next_size</code><span class="sig-paren">(</span><em>dim_x</em>, <em>dim_y</em>, <em>k</em>, <em>s</em>, <em>p</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/conv_decoders.html#SimpleConvDecoder.next_size"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.conv_decoders.SimpleConvDecoder.next_size" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

</dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.conv_decoders.infer_conv_size">
<code class="descclassname">cortex.built_ins.networks.conv_decoders.</code><code class="descname">infer_conv_size</code><span class="sig-paren">(</span><em>w</em>, <em>k</em>, <em>s</em>, <em>p</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/conv_decoders.html#infer_conv_size"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.conv_decoders.infer_conv_size" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.convnets">
<span id="cortex-built-ins-networks-convnets-module"></span><h2>cortex.built_ins.networks.convnets module<a class="headerlink" href="#module-cortex.built_ins.networks.convnets" title="Permalink to this headline">¶</a></h2>
<p>Convoluational encoders</p>
<dl class="class">
<dt id="cortex.built_ins.networks.convnets.SimpleConvEncoder">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.convnets.</code><code class="descname">SimpleConvEncoder</code><span class="sig-paren">(</span><em>shape</em>, <em>dim_out=None</em>, <em>dim_h=64</em>, <em>fully_connected_layers=None</em>, <em>nonlinearity='ReLU'</em>, <em>output_nonlinearity=None</em>, <em>f_size=4</em>, <em>stride=2</em>, <em>pad=1</em>, <em>min_dim=4</em>, <em>n_steps=None</em>, <em>spectral_norm=False</em>, <em>last_conv_nonlinearity=True</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/convnets.html#SimpleConvEncoder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.convnets.SimpleConvEncoder" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#cortex.built_ins.networks.base_network.BaseNet" title="cortex.built_ins.networks.base_network.BaseNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">cortex.built_ins.networks.base_network.BaseNet</span></code></a></p>
<dl class="method">
<dt id="cortex.built_ins.networks.convnets.SimpleConvEncoder.next_size">
<code class="descname">next_size</code><span class="sig-paren">(</span><em>dim_x</em>, <em>dim_y</em>, <em>k</em>, <em>s</em>, <em>p</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/convnets.html#SimpleConvEncoder.next_size"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.convnets.SimpleConvEncoder.next_size" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.convnets.SimpleNet">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.convnets.</code><code class="descname">SimpleNet</code><a class="reference internal" href="_modules/cortex/built_ins/networks/convnets.html#SimpleNet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.convnets.SimpleNet" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.convnets.SimpleNet.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/convnets.html#SimpleNet.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.convnets.SimpleNet.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.convnets.infer_conv_size">
<code class="descclassname">cortex.built_ins.networks.convnets.</code><code class="descname">infer_conv_size</code><span class="sig-paren">(</span><em>w</em>, <em>k</em>, <em>s</em>, <em>p</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/convnets.html#infer_conv_size"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.convnets.infer_conv_size" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.fully_connected">
<span id="cortex-built-ins-networks-fully-connected-module"></span><h2>cortex.built_ins.networks.fully_connected module<a class="headerlink" href="#module-cortex.built_ins.networks.fully_connected" title="Permalink to this headline">¶</a></h2>
<p>Simple dense network encoders</p>
<dl class="class">
<dt id="cortex.built_ins.networks.fully_connected.FullyConnectedNet">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.fully_connected.</code><code class="descname">FullyConnectedNet</code><span class="sig-paren">(</span><em>dim_in</em>, <em>dim_out=None</em>, <em>dim_h=64</em>, <em>dim_ex=None</em>, <em>nonlinearity='ReLU'</em>, <em>n_levels=None</em>, <em>output_nonlinearity=None</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/fully_connected.html#FullyConnectedNet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.fully_connected.FullyConnectedNet" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#cortex.built_ins.networks.base_network.BaseNet" title="cortex.built_ins.networks.base_network.BaseNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">cortex.built_ins.networks.base_network.BaseNet</span></code></a></p>
</dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.modules">
<span id="cortex-built-ins-networks-modules-module"></span><h2>cortex.built_ins.networks.modules module<a class="headerlink" href="#module-cortex.built_ins.networks.modules" title="Permalink to this headline">¶</a></h2>
<p>General purpose modules</p>
<dl class="class">
<dt id="cortex.built_ins.networks.modules.Pipeline">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.modules.</code><code class="descname">Pipeline</code><span class="sig-paren">(</span><em>networks</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/modules.html#Pipeline"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.modules.Pipeline" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.modules.Pipeline.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/modules.html#Pipeline.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.modules.Pipeline.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.modules.View">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.modules.</code><code class="descname">View</code><span class="sig-paren">(</span><em>*shape</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/modules.html#View"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.modules.View" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.modules.View.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/modules.html#View.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.modules.View.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.resnets">
<span id="cortex-built-ins-networks-resnets-module"></span><h2>cortex.built_ins.networks.resnets module<a class="headerlink" href="#module-cortex.built_ins.networks.resnets" title="Permalink to this headline">¶</a></h2>
<p>Residual encoder / decoder</p>
<dl class="class">
<dt id="cortex.built_ins.networks.resnets.ConvMeanPool">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.resnets.</code><code class="descname">ConvMeanPool</code><span class="sig-paren">(</span><em>dim_in</em>, <em>dim_out</em>, <em>f_size</em>, <em>nonlinearity=None</em>, <em>prefix=''</em>, <em>spectral_norm=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#ConvMeanPool"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.ConvMeanPool" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.resnets.ConvMeanPool.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#ConvMeanPool.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.ConvMeanPool.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.resnets.MeanPoolConv">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.resnets.</code><code class="descname">MeanPoolConv</code><span class="sig-paren">(</span><em>dim_in</em>, <em>dim_out</em>, <em>f_size</em>, <em>nonlinearity=None</em>, <em>prefix=''</em>, <em>spectral_norm=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#MeanPoolConv"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.MeanPoolConv" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.resnets.MeanPoolConv.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#MeanPoolConv.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.MeanPoolConv.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.resnets.ResBlock">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.resnets.</code><code class="descname">ResBlock</code><span class="sig-paren">(</span><em>dim_in</em>, <em>dim_out</em>, <em>dim_x</em>, <em>dim_y</em>, <em>f_size</em>, <em>resample=None</em>, <em>name='resblock'</em>, <em>nonlinearity='ReLU'</em>, <em>spectral_norm=False</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#ResBlock"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.ResBlock" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.resnets.ResBlock.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#ResBlock.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.ResBlock.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.resnets.ResDecoder">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.resnets.</code><code class="descname">ResDecoder</code><span class="sig-paren">(</span><em>shape</em>, <em>dim_in=None</em>, <em>f_size=3</em>, <em>dim_h=64</em>, <em>n_steps=3</em>, <em>nonlinearity='ReLU'</em>, <em>output_nonlinearity=None</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#ResDecoder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.ResDecoder" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.resnets.ResDecoder.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em>, <em>nonlinearity=None</em>, <em>**nonlinearity_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#ResDecoder.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.ResDecoder.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.resnets.ResEncoder">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.resnets.</code><code class="descname">ResEncoder</code><span class="sig-paren">(</span><em>shape</em>, <em>dim_out=None</em>, <em>dim_h=64</em>, <em>fully_connected_layers=None</em>, <em>f_size=3</em>, <em>n_steps=3</em>, <em>nonlinearity='ReLU'</em>, <em>output_nonlinearity=None</em>, <em>spectral_norm=False</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#ResEncoder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.ResEncoder" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#cortex.built_ins.networks.base_network.BaseNet" title="cortex.built_ins.networks.base_network.BaseNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">cortex.built_ins.networks.base_network.BaseNet</span></code></a></p>
</dd></dl>

<dl class="class">
<dt id="cortex.built_ins.networks.resnets.UpsampleConv">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.resnets.</code><code class="descname">UpsampleConv</code><span class="sig-paren">(</span><em>dim_in</em>, <em>dim_out</em>, <em>f_size</em>, <em>nonlinearity=None</em>, <em>prefix=''</em>, <em>spectral_norm=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#UpsampleConv"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.UpsampleConv" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.resnets.UpsampleConv.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/resnets.html#UpsampleConv.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.resnets.UpsampleConv.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.tv_models_wrapper">
<span id="cortex-built-ins-networks-tv-models-wrapper-module"></span><h2>cortex.built_ins.networks.tv_models_wrapper module<a class="headerlink" href="#module-cortex.built_ins.networks.tv_models_wrapper" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="cortex.built_ins.networks.tv_models_wrapper.AlexNet">
<em class="property">class </em><code class="descclassname">cortex.built_ins.networks.tv_models_wrapper.</code><code class="descname">AlexNet</code><span class="sig-paren">(</span><em>shape</em>, <em>dim_out=None</em>, <em>fully_connected_layers=None</em>, <em>nonlinearity='ReLU'</em>, <em>n_steps=None</em>, <em>**layer_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/tv_models_wrapper.html#AlexNet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.tv_models_wrapper.AlexNet" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchvision.models.alexnet.AlexNet</span></code></p>
<dl class="method">
<dt id="cortex.built_ins.networks.tv_models_wrapper.AlexNet.forward">
<code class="descname">forward</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/tv_models_wrapper.html#AlexNet.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.tv_models_wrapper.AlexNet.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks.utils">
<span id="cortex-built-ins-networks-utils-module"></span><h2>cortex.built_ins.networks.utils module<a class="headerlink" href="#module-cortex.built_ins.networks.utils" title="Permalink to this headline">¶</a></h2>
<p>Utils for networks</p>
<dl class="function">
<dt id="cortex.built_ins.networks.utils.apply_nonlinearity">
<code class="descclassname">cortex.built_ins.networks.utils.</code><code class="descname">apply_nonlinearity</code><span class="sig-paren">(</span><em>x</em>, <em>nonlinearity</em>, <em>**nonlinearity_args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/utils.html#apply_nonlinearity"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.utils.apply_nonlinearity" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.utils.finish_layer_1d">
<code class="descclassname">cortex.built_ins.networks.utils.</code><code class="descname">finish_layer_1d</code><span class="sig-paren">(</span><em>models</em>, <em>name</em>, <em>dim_out</em>, <em>dropout=False</em>, <em>layer_norm=False</em>, <em>batch_norm=False</em>, <em>nonlinearity=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/utils.html#finish_layer_1d"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.utils.finish_layer_1d" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.utils.finish_layer_2d">
<code class="descclassname">cortex.built_ins.networks.utils.</code><code class="descname">finish_layer_2d</code><span class="sig-paren">(</span><em>models</em>, <em>name</em>, <em>dim_x</em>, <em>dim_y</em>, <em>dim_out</em>, <em>dropout=False</em>, <em>layer_norm=False</em>, <em>batch_norm=False</em>, <em>nonlinearity=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/utils.html#finish_layer_2d"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.utils.finish_layer_2d" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

<dl class="function">
<dt id="cortex.built_ins.networks.utils.get_nonlinearity">
<code class="descclassname">cortex.built_ins.networks.utils.</code><code class="descname">get_nonlinearity</code><span class="sig-paren">(</span><em>nonlinearity=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cortex/built_ins/networks/utils.html#get_nonlinearity"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#cortex.built_ins.networks.utils.get_nonlinearity" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

</div>
<div class="section" id="module-cortex.built_ins.networks">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-cortex.built_ins.networks" title="Permalink to this headline">¶</a></h2>
</div>
</div>


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